Doctor of Philosophy in Computing and Information Sciences
Evelyn Rozanski, Ph.D., Interim Associate Dean, Graduate Studies and Research
(585) 475-6147, Rozanski@it.rit.edu
This use-inspired basic research degree is designed to produce independent scholars, well-prepared educators, and cutting-edge researchers poised to excel in their work within interdisciplinary environments and industries. The degree highlights two of the most unique characteristics of the Golisano—the breadth of its program offerings and its scholarly focus on discovering solutions to real-world problems by balancing theory and practice.
The Ph.D. program focuses on the theoretical and practical aspects of cyberinfrastructure as applied to specific problems across multiple domains. It is a blend of the intra-disciplinary computing knowledge areas of interaction, informatics, and infrastructure, with interdisciplinary domain areas.
Cyberinfrastructure
The National Science Foundation defines cyberinfrastructure (CI) as a comprehensive infrastructure integrating hardware, data, networks, and digitally-enabled sensors to provide secure, efficient, reliable, accessible, usable, and interoperable suites of software and middleware services and tools. This Ph.D. program is playing a leadership role in the CI research area by providing human-centered CI tools for the science and engineering communities. The world-class CI tools and services focus on such areas as high performance computing; data analysis and visualization; cyber-services and virtual environments; and, learning and knowledge management.
Intra-disciplinary knowledge areas
The intra-disciplinary computing knowledge areas are organized into three areas: interaction, informatics, and infrastructure. Interaction refers to topics related to the combined action of two or more entities (human or computational) that both affect one another and work together when facilitated by technology. It in turn encompasses several subtopics relating to how people and technology interact and interface. There are several common threads that weave through all of the areas Many of them rely heavily and build upon foundations in the social, cognitive, and behavioral sciences with an emphasis on understanding human phenomena and social/organizational phenomena. To some extent, these fields follow an engineering approach to the design of interactions in which solutions are based on rules and principles derived from research and practice, but require analyses that go beyond the analytical approach. From this perspective, solutions can be measured and evaluated against goals and intended outcomes. However, while efficiency and effectiveness are often the watchwords of these fields in practice, this is also where science meets art in computing, and creative design, and sensitivity to human needs and aesthetics are critical.
Informatics is the study of computational/algorithmic techniques applied to the management and understanding of data-intensive systems. It focuses on the capture, storage, processing, analysis, and interpretation of data. Topics include primarily algorithms, complexity, and discovery informatics. Data storage and processing require investigation into tools and techniques for modeling, storage, and retrieval. Analysis and understanding require the development of tools and techniques for the symbolic modeling, simulation, and visualization of data. The increased complexity of managing vast amounts of data requires a better understanding of the fundamentals of computation. These fundamentals include complexity theory to determine the inherent limits of computation, communication, cryptography, and the design and analysis of algorithms to obtain optimal solutions within the limits identified.
Infrastructure comprises aspects primarily related to hardware, software (both system software and applications), communications technology, and their integration with computing systems through applications. The focus is on the best organization of these elements to provide optimal architectural solutions. It includes, on the hardware side, system-level design (e.g., for system-on-a-chip solutions) and their building block components. On the software side, it covers all aspects of systems and applications software development, including specification and design languages and standards; validation and prototyping, and multi-dimensional Quality-of-Service management; software product lines, model-driven architectures, component-based development, and domain-specific languages; and project estimation, tracking, and oversight. The communications subtopic includes sensor networks and protocols, as well as active networks, wireless networks, mobile networks, configurable networks, and high speed networks; as well as, network security and privacy, quality of service, reliability, service discovery, and integration and interworking across heterogeneous networks. At the system level there are issues related to conformance and certification; system dependability, fault tolerance, verifiable adaptability, and reconfigurable systems; and real-time, self-adaptive, self-organizing, autonomic systems.
Interdisciplinary domain areas
The Ph.D. program also focuses on the interaction between computing and non-computing disciplines, or areas of domain-specific computing, in science, engineering, arts, humanities, and business. By incorporating domain-specific computing, following the philosophy of use-inspired research, the research conducted in this program applies computing and information science principles to the solution of problems in application domains that lie outside of the scope of the traditional computing discipline. The research requirement incorporates fundamental concepts in cyberinfrastructure necessary for understanding the problems commonly encountered in advancing scientific discovery and product development in cross-disciplinary domains.
Some of the interdisciplinary domain research areas are: astro-informatics; bio-medical informatics; computational biology; computational science; environmental informatics; services sciences; and, electronic commerce.
Admission requirements
Entry into the Ph.D. program is typically directly from a baccalaureate program. Students with graduate degrees are also encouraged to apply.
Admission to the Ph.D. in computing and information sciences is highly competitive and successful applicants will, in general, have records considerably stronger in breadth or quality than the minimum standards suggest. Applicants should also be aware that meeting the requirements does not guarantee admission.
Applicants will be evaluated on the basis of their prior academic record and their potential for creative research. Admissions decisions are made by the admissions committee, which is comprised of the faculty members of the program. Admissions decisions will generally be made in the winter for admissions in the Fall quarter.
Minimum requirements for consideration include:
- Baccalaureate degree or its recognized equivalent. Since the doctoral program in computing and information sciences encompasses a wide variety of disciplines, we seek students with diverse backgrounds. While most students will come from a computing-related discipline, students in engineering, science, humanities, fine arts, business, and other disciplines along with computing backgrounds are encouraged to apply.
- Strong record of academic achievement as indicated by official transcripts.
- Mathematical skills equivalent to college-level courses in discrete mathematics, and probability and statistics.
- Recommendations from at least two individuals who are well-qualified to assess the student’s potential for success in a doctoral program.
- Professional or research paper writing sample(s), if available.
- Written statement defining the student’s research interests.
- Current resume with current position, if applicable.
- Optional portfolio of previous work.
GRE Scores
Recent results (within five years) of the Graduate Record Examination (GRE) are required.
TOEFL Scores
The Test of English as a Foreign Language score is required for every applicant for whom English is not the native language. A score of at least 570 (paper-based), 88 (Internet-based), or 230 (computer-based) is required. Exceptions can be made for an applicant whose academic record is strong. Upon arrival at RIT, students whose native language is not English may be required to take the Michigan English Test and follow the recommendations of RIT’s English Language Center.
Interview
An interview by one or more of the doctoral program faculty and/or admissions committee will be required for candidates considered for admission prior to final selection. This interview may be via telephone.
Transfer Credit
Students transferring into the program from a masters program in a computing and information sciences discipline, or in a related domain-specific discipline, may be granted up to 28 quarter-based credit hours towards the Ph.D. degree requirements. However, students are not eligible to earn an additional master’s degree if the student already holds an MS degree in a computing and information sciences or related field from RIT or another university.
The transfer credit evaluation will not be made until after the first year of study. Consideration for transfer credit will include the appropriateness to the student’s intra and inter-disciplinary program of study and research interests.
Assistantships
A limited number of assistantships, including tuition and stipend, are available and awarded on a competitive basis. Students working on funded research projects will be required to be available during the day for project commitments
Curriculum
The program requires a minimum of 111 quarter-credit hours beyond the baccalaureate level. These credit hours are comprised of graduate-level course work, including seminar attendance and research credits.
Required Courses
4040-810 Research Methods
4040-820 Discovery
4040-830 Connectivity
4040-840 Security and Trust
4040-850 Design
4040-900 Collaborative Practicum
4040-801 Student Research Seminar*
4040-896 Cyberinfrastructure Colloquium
4040-807 Teaching Skills Workshop I
4040-808 Teaching Skills Workshop II
4040-809 Teaching Skills Apprenticeship
*Student Research Seminar (4040-801) may be taken more than once.
Intra-disciplinary specialty electives (20 quarter credit hours)
The curriculum draws from the offering of the graduate programs within the Golisano College as well as from domain-specific graduate offerings from other colleges at RIT. A large selection of graduate level courses already exists in the college, as well as in other colleges at RIT. These courses are taught on a regular basis in support of the various master’s programs being offered, and are the bulk of the elective courses for students’ area of specialization.
Students are required to take courses from two of the three knowledge specialty areas: interaction, informatics or infrastructure.
Interaction
Some of the specialties available in this area are:
4004-745 Foundations of Human-computer Interaction
4004-748 Usability Engineering
4004-749 Usability Testing
4004-755 Advanced Topics in HCI
4002-765 User-centered Design Methods
4002-892 CSCW and Groupware
Computer-Based Instructional Systems – Courses in this area will allow students to conduct research on the effectiveness of instructional systems and be involved in the development and evaluation of new instructional tools.
4002-723 Interactive Courseware
4002-820 Simulations and Learning Environments
4002-828 Intelligent Computer Based Instruction
4002-812 Knowledge and Content Objects
4002-728 Models of Human Performance
4002-845 Economics of Human Performance
Informatics
Some of the specialties available in this area are:
Core Informatics – Courses in this area cover the increased complexity of managing vast
amounts of data.
4005-700 Foundations of Computing Theory
4005-709 Combinatorial Computing
0301-794 Information Theory
4005-704 Complexity Theory
4005-705 Cryptography
4005-780 Computer System Security
4005-735 Parallel Computing
4010-750 Software Modeling
4005-800 Theory of Computer Algorithms
Discovery Informatics – Courses in this area study the closely related problems of data
management, knowledge discovery, and pattern recognition.
4005-771 Database Systems
4005-759 Data Mining
4005-759 Database Management Concepts
4005-772 Database Systems Implementation
4005-779 Secure Database Systems
Intelligent Systems – Courses in this area focus on developing models that are biologically
inspired and that leverage current knowledge in cognitive science,
neuroscience, computer science, and engineering with the goal of developing
systems that understand a given environment.
4005-750 Introduction to Artificial Intelligence
4005-759 Biologically Inspired Intelligent Systems
4005-755 Neural Networks and Machine Learning
0301-770 Pattern Recognition
4005-757 Introduction to Computer Vision
4005-759 Advanced Computer Vision
Infrastructure
Some of the specialties available in this area are:
Networks and Security – Courses in this area provide in-depth study in design, modeling, and
implementation in the security-related and performance analysis aspects of data
and communication networks.
0306-710 Network Design, Modeling and Simulation
4002-817 Emerging Network Technologies
4005-742 Ad-hoc Networks
4002-755 Secure Wireless and Wired Data Networks
4005-743 Secure Operating Systems and Networks
0306-772 Wireless Networks
4002-760 Computer Viruses and Malicious Software
4002-780 Computer System Security
4002-841 Advanced Computer Forensics
4002-882 Enterprise Security
Digital Systems and VLSI – Courses in this area cover the design, modeling, and evaluation of
modern computing systems, including hardware, software, and their integration.
0306-756 Multiple Processor Systems
0306-722 Advanced Computer Architecture
0306-772 Embedded and Real-time Systems
0306-731 VLSI Design Projects
0306-772 Advanced Digital Modeling
0301-730 Advanced Analog IC Design
0301-726 Mixed Signal IC Design
4005-730 Distributed Systems I
Inter-disciplinary Domain Courses (12 quarter credit hours) in an area directly related to the student’s research project. Example areas include: astro-informatics; bio-medical informatics; computational biology; computational science; environmental informatics; services sciences; and, electronic commerce.
Advanced Electives (8 quarter credit hours), with adviser approval, are designed to further an intra-disciplinary computing specialty or inter-disciplinary domain area.
Dissertation (32 quarter credit hours)
Students will be required to conduct original, use-inspired research involving two of the three knowledge areas of interaction, informatics, and infrastructure, and apply them to a domain.
Residency Requirement
Two years of full-time residency (minimum of 9 quarter credit hours for six consecutive quarters, not including summer) and register each quarter during their residency for the Student Research Seminar course.
Assessments
Each student must pass four examinations in the following order:
- Breadth Assessment after the core course work (after the first year)
- Depth Assessment after the computing specialization and domain course work (typically after the second year)
- Thesis Proposal Defense (committee approval) after the thesis proposal is written
- Dissertation Defense after all course work, research and the first three assessments have been successfully completed and the dissertation written